Presentation

Introduction: Paper and background

  • Circulating Exosomal microRNAs as Predictive Biomarkers of Neoadjuvant Chemotherapy Response in Breast Cancer

Neoadjuvant chemotherapy (NACT) | an increasingly used approach for treatment of breast cancer |
Circulating Exosomal microRNAs(miRNA) | small RNA molecules circulating in bodily fluids, potentially serving as biomarkers for treatment response after NACT |
Pathological Complete Response (pCR) | absence of active cancer cells in a tissue from the tumor site after NACT |
Non-Pathological Complete Response (non-pCR) | presence of active cancer cells in a tissue from the tumor site after the treatment |

  • The purpose of the study: to investigate whether circulating exosomal microRNAs could predict pCR in breast cancer patients treated with NACT

Todorova, Valentina K., et al. “Circulating exosomal microRNAs as predictive biomarkers of neoadjuvant chemotherapy response in breast cancer.” Current Oncology 29.2 (2022): 613-630.

  • Purple

Todorova, Valentina K., et al. “Circulating exosomal microRNAs as predictive biomarkers of neoadjuvant chemotherapy response in breast cancer.” Current Oncology 29.2 (2022): 613-630.

Introduction: pCR & nonpCR

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Materials and methods: Flowchart

Methods: Metadata & Describe

Methods: Describe

Methods: Gene Expression Analysis

Methods: Virtual pull-down and Gene Enrichement Analysis

  • Virtual pull-down:
library(DiscoNet)
network_pCR <- virtual_pulldown(
  seed_nodes = seed, 
  database = string_database, 
  id_type = "hgnc", 
  string_confidence_score = 700) # default value
  • Community detection
library(DiscoNet)
communities_list <- community_detection(
  graph_object, 
  algorithm = "mcode", # specifies algorithm, in this case MCODE
  D = 0.05, # threshold of weight percentage of the vertex to be use by MCODE standard value
  haircut = TRUE) # removes the nodes that are only connected to a single node in the community detected
  • Over representation analysis
library(fgsea)

ora_result_nonpCR <- fora(
    pathways = biological_process_list, 
    genes = gense_in_each_community, 
    universe = all_genes_in_analysis, 
    minSize = 10
)

Results: Gene Expression Analysis

Results: Virtual pull-down

  • Pre vs. Post Treatment:
    • The nonpCR Group has 5 potential complexes or networks with upregulated or downregulated activity when comparing pre- and post-treatment
    • The pCR Group has 11 potential complexes or networks with upregulated or downregulated activity when comparing pre- and post-treatment
  • Example plots:

Results: Gene Enrichement Analysis

  • For each relevant community in pCR and non_pCR the main enriched biological processes were identified
  • Representative plots:

Discussion and Conclusion